As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts.

As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components.

You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms).

Embedded software development experience is a plus.

You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs.

Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization.

Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company.

This means you will get to directly contribute to the development of Anduril’s next-generation products and services.

So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

Key Responsibilities:

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.

• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.

• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.

• Support Anduril- and customer-funded R&D efforts.

• Participate in field experiments and technology demonstrations.

Requirements:

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.

• Proven software architecture and design skills.

• Ability to quickly understand and navigate complex systems and established codebases.

• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).

• Web app development (e.g., React, Angular, or Vue).

• Cloud development (e.g., AWS, Azure, or GCP).

• Data modeling and wrangling.

• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory).

• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).

• API development and integration (e.g., REST, GraphQL).

• Containerization technologies (e.g., Docker, Kubernetes).

• Software development on Linux and Windows.

• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.

• Experience with Git version control, build tools, and CI/CD pipelines.

• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.

• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.

• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.

• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.

Preferred Qualifications:

• BS in Computer Science, Engineering, or similar field.

• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).

• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).

• Mobile app development (e.g., iOS or Android).

• Embedded software development experience.

• Willingness to travel up to approximately 10% US

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You'll be working on large-scale ML systems from the ground up, making safe, steerable, trustworthy systems. You'll be excited to write code when you understand the research context and more broadly why it's important.

Strong candidates may also have experience with high performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, or OS internals, language modeling with transformers, reinforcement learning, and large-scale ETL.

Representative projects may include optimizing the throughput of a new attention mechanism, comparing the compute efficiency of two Transformer variants, making a Wikipedia dataset in a format models can easily consume, scaling a distributed training job to thousands of GPUs, writing a design doc for fault tolerance strategies, and creating an interactive visualization of attention between tokens in a language model.

The annual compensation range for this role is $350,000-$500,000 USD.

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As an Engineering Manager on Anthropic's performance and scaling teams, you will be responsible for ensuring the team is identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

Requirements:

• 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Background in machine learning, AI, or a similar related technical field
• Deeply interested in the potential transformative effects of advanced AI systems and committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Quick learner, capable of understanding and contributing to discussions on complex technical topics
• Experience managing teams through periods of rapid growth and change

Nice to have:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Compensation:

The annual compensation range for this role is $425,000-$560,000 USD.

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The Common Engineering Components (CEC) team, part of Synopsys Central Engineering, develops and maintains productivity-enhancing platforms, tools, and services enabling Synopsys R&D engineers, Field Application Engineers (FAEs), and customers to efficiently identify, diagnose, and resolve issues in Synopsys' Electronic Design Automation (EDA) tools. Our work is critical to the performance and scalability of EDA solutions used in silicon chip design.

We are looking for a Senior Staff Software Engineer to join our team. As a Senior Staff Software Engineer, you will be responsible for delivering enterprise-scale software solutions to internal and external stakeholders, ensuring reliability and performance at every stage. You will collaborate with multiple global engineering teams to achieve common goals and successful project delivery. You will define technical requirements and drive implementation of next-generation productivity platforms. You will mentor engineers, fostering a culture of technical excellence, collaboration, and innovation within the team.

You will utilize C/C++, Python, Unix/Linux system-level knowledge, and advanced debugging and performance profiling tools to deliver robust, scalable solutions and resolve critical issues efficiently. You will accelerate Synopsys' capability to deliver cutting-edge solutions for customers and partners worldwide. You will enable seamless integration of advanced computing platforms into chip design and verification workflows. You will drive operational efficiency and scalability for mission-critical applications and services. You will influence technology strategy and architecture decisions, shaping the future of Synopsys' product offerings. You will empower engineering teams through mentorship, fostering innovation and technical growth. You will enhance customer satisfaction by delivering reliable, high-performance software solutions tailored to evolving industry needs.

You will have 8–14 years of professional software development experience, ideally in High Performance Computing (HPC) or large-scale systems. You will have strong Unix/Linux systems programming background, including multithreading, synchronization, sockets, and inter-process communication (IPC). You will have proven experience designing and working with distributed systems, including networking, databases, and containerized environments. You will have proficiency in C/C++ and Python, with hands-on experience using debugging and performance profiling tools. You will have excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.

You will be an inclusive leader and collaborator, committed to fostering diverse perspectives and teamwork. You will be analytical and detail-oriented, with a passion for solving challenging technical problems. You will be adaptable and proactive, able to thrive in dynamic, rapidly evolving environments. You will be curious and innovative, always seeking new ways to leverage technology for impactful results. You will be a mentor and coach, dedicated to supporting the growth and development of others.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role:

Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:

We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification.

Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us.

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and paid time off, and a comprehensive benefits package.

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Microsoft AI are looking for a talented Member of Technical Staff, High Performance Computing Engineer at their London office. This role sits at the heart of building and scaling the infrastructure that trains their frontier models and powers the next evolution of their personal AI, Copilot. You'll work directly with researchers and engineers to support their workloads, troubleshoot cluster usage issues, and triage failed or underperforming jobs to resolution.

About the Role

As a Member of Technical Staff, High Performance Computing Engineer, you will design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings. You will own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale. You will serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.

Accountabilities

• Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
• Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.
• Serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters.
• 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.).
• 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP.

Technical skills:

• Experience with LLM training clusters.
• Experience working with AI platforms, frameworks, and APIs.
• Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.

Personal attributes:

• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.

Benefits

• Competitive salary and benefits package.
• Opportunity to work with a leading technology company and contribute to HERE's mission.
• Collaborative and dynamic work environment.
• Professional development opportunities.

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Microsoft AI are looking for experienced Member of Technical Staff, High Performance Computing Engineers to help build and scale the infrastructure that trains their frontier models and powers the next evolution of their personal AI, Copilot.

About the Role

This role offers the unique opportunity to work on some of the largest scale supercomputers in the world – a rare chance to operate at such a significant scale. As a Member of Technical Staff, High Performance Computing Engineer, you will design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings. You will own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.

Accountabilities

• Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
• Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters.
• 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.).
• 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP.

Technical skills:

• Experience with LLM training clusters.
• Experience working with AI platforms, frameworks, and APIs.
• Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.

Personal attributes:

• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.

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What you'll do

As a Software Developer, you will be responsible for developing, implementing, and maintaining combustion and reactive-flow models within a finite volume CFD solver environment. You will also enhance numerical algorithms to improve stability, accuracy, and computational performance, including adaptation for parallel and high performance computing environments.

What you need

• PhD in Mechanical Engineering, Chemical Engineering, Physics, Computational Engineering, or a related technical discipline
• Strong theoretical understanding of combustion, fluid mechanics, thermodynamics, and heat transfer
• Experience with finite volume CFD methods and numerical discretization techniques
• Proficiency in C++ or Fortran for scientific or engineering software development; additional experience with Python is advantageous

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